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Analysing inter-relationships among water, governance, human development variables in developing countries: WatSan4Dev database coherency analysis

Author(s): C. Dondeynaz | C. Carmona Moreno | J. J. C├ęspedes Lorente

Journal: Hydrology and Earth System Sciences Discussions
ISSN 1812-2108

Volume: 9;
Issue: 1;
Start page: 485;
Date: 2012;
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The "Integrated Water Resources Management" principle was formally laid down at the International Conference on Water and Sustainable development in Dublin 1992. One of the main results of this conference is that improving Water and Sanitation Services (WSS), being a complex and interdisciplinary issue, passes through collaboration and coordination of different sectors (environment, health, economic activities, governance, and international cooperation). These sectors influence or are influenced by the access to WSS. The understanding of these interrelations appears as crucial for decision makers in the water sector. In this framework, the Joint Research Centre (JRC) of the European Commission (EC) has developed a new database (WatSan4Dev database) containing 45 indicators (called variables in this paper) from environmental, socio-economic, governance and financial aid flows data in developing countries. This paper describes the development of the WatSan4Dev dataset, the statistical processes needed to improve the data quality; and, finally, the analysis to verify the database coherence is presented. At the light of the first analysis, WatSan4Dev Dataset shows the coherency among the different variables that are confirmed by the direct field experience and/or the scientific literature in the domain. Preliminary analysis of the relationships indicates that the informal urbanisation development is an important factor influencing negatively the percentage of the population having access to WSS. Health, and in particular children health, benefits from the improvement of WSS. Efficient environmental governance is also an important factor for providing improved water supply services. The database would be at the base of posterior analyses to better understand the interrelationships between the different indicators associated in the water sector in developing countries. A data model using the different indicators will be realised on the next phase of this research work.
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